Flotation is used to extract non-ferrous metals from the rock. The rock is crushed to powder, mixed with water and foamed. Specialists study various froth parameters such as speed, bubble size, color, froth stability, etc. to understand and describe the flotation process.

Task: determination of various foam parameters during the flotation process and transferring them to specialists for analysis.

Our solution: we use a combination of classical computer vision methods with deep learning methods for extracting visual information about flotation process. Then we display on the dashboard the information necessary for specialists to optimize the process in order to improve key indicators.

Advantages

• large number of defined parameters
• technical possibility of predicting foam trajectory for a few seconds ahead
• work in difficult industrial conditions

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